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Auteur Z. Cvijetinović |
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Weighted coordinate transformation formulated by standard least-squares theory / D. Mihajlovic in Survey review, vol 49 n° 356 (November 2017)
[article]
Titre : Weighted coordinate transformation formulated by standard least-squares theory Type de document : Article/Communication Auteurs : D. Mihajlovic, Auteur ; Z. Cvijetinović, Auteur Année de publication : 2017 Article en page(s) : pp 328 - 345 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] méthode des moindres carrés
[Termes IGN] pondération
[Termes IGN] transformation de coordonnéesRésumé : (Auteur) This paper presents a universal model of weighted coordinate transformation, i.e. transformation considering the errors of coordinates in both coordinate systems. It is intrinsically one of the typical examples of ‘error-in-variables’ (EIV) models. The proposed method of LS theory application on weighted coordinate transformation does not impose any constraints on the form of functional relationship among stochastic variables. Since the basic idea is to generalise Gauss–Markov model (GMM) by introduction of so-called ‘total residuals’, the proposed procedure is named ‘Generalised Gauss–Markov model’. Formulation of expressions for estimation of unknown transformation parameters is theoretically confirmed using the Gauss–Helmert model (GHM) and three different modifications of the GMM. The proposed procedure is in its essence a strict solution to total least-squares (unweighted) and weighted total least-squares problem in coordinate transformation. This thesis is experimentally confirmed by comparison of its results with those found in four characteristic examples from the literature. Numéro de notice : A2017-555 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/00396265.2016.1173329 En ligne : https://doi.org/10.1080/00396265.2016.1173329 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86616
in Survey review > vol 49 n° 356 (November 2017) . - pp 328 - 345[article]